This paper addresses the integration of artificial intelligence (AI) with multi-criteria decision-making (MCDM) approaches in procurement under the conditions of high uncertainty characteristic of VUCA/BANI environments. Based on a structured literature review, a conceptual causal loop diagram (CLD) is developed to model the relationships between external factors, internal organizational conditions, and AI-supported decision-making capabilities. The results indicate that procurement decisions should be understood as a dynamic system influenced by interdependencies between variables such as supplier base availability, market volatility, and procurement maturity. The model identifies key drivers of cost, supply-chain resilience, and decision quality, highlighting the central role of highly connected variables. The study contributes to the field by proposing an integrated framework supporting the adoption of AI in procurement decision processes. The proposed model provides a foundation for further empirical research and may support organizations in the gradual implementation of data-driven approaches in procurement management. Future research should focus on human-centric AI, regulatory alignment, and continuous system improvement to ensure sustainable and effective adoption.